7 Best Data Marketplace Tools in 2026

Data is becoming easier to collect but harder to discover and use efficiently. Organizations may have thousands of internal datasets, third-party data products, APIs, and analytical assets spread across different systems, making it difficult for teams to know what data exists, whether it is trustworthy, and how to access it.

A data marketplace provides a more structured way to solve that discovery and access problem. Data marketplace tools are platforms that help organizations publish, discover, share, access, buy, sell, or distribute datasets and other data products.

The market includes both cloud-native marketplaces and independent platforms. Snowflake Marketplace, Databricks Marketplace, AWS Data Exchange, and Google Cloud’s Analytics Hub are closely connected to their respective data platforms, while Datarade, Dawex, and Narrative provide broader data-commerce or data-exchange capabilities. Some focus primarily on data discovery and consumption, while others also support providers with publishing, licensing, pricing, access management, and monetization.

This guide covers 7 of the best data marketplace tools in 2026. We evaluate them based on data discovery, publishing, data sharing, access controls, integrations, data-product management, governance, marketplace capabilities, monetization options, pricing, and open-source availability.

Why Do You Need Data Marketplace Tools?

• Make data easier to discover: Give users a central place to search for internal or external datasets.
• Reduce data silos: Connect data producers and consumers without relying on manual requests or scattered documentation.
• Share data securely: Provide controlled ways to distribute datasets between teams, organizations, or business partners.
• Buy third-party data: Help teams evaluate and acquire external datasets from multiple providers.
• Monetize data products: Give data providers infrastructure for publishing, pricing, licensing, and selling datasets.
• Create self-service access: Let authorized users find and request data without depending on data engineering teams for every request.
• Improve data governance: Add ownership, metadata, permissions, policies, and other controls around shared data.
• Compare data providers: Help buyers evaluate multiple datasets and providers before committing to a purchase.
• Simplify data delivery: Provide direct access through files, APIs, shares, or connected data platforms.
• Support data products: Turn curated datasets and analytical assets into reusable products with defined access and ownership.

Top 7 Data Marketplace Tools: Comparison

Data marketplace platforms differ considerably in how they handle discovery, delivery, governance, and commercial data exchange. Cloud-native options can provide direct access within an existing data platform, while independent marketplaces can provide broader access to external providers and datasets.

Best 7 Data Marketplace Tools in 2026

The tools below cover cloud-native data marketplaces, enterprise data exchanges, and independent data-commerce platforms. Together, they support use cases ranging from discovering third-party datasets and sharing data internally to publishing commercial data products and building data monetization channels.

#1 Snowflake Marketplace

Snowflake Marketplace is a data and application marketplace built into the Snowflake Data Cloud. It allows organizations to discover and access third-party datasets, data products, applications, and other offerings while using Snowflake’s underlying data-sharing capabilities.

A major advantage of the marketplace is that consumers can access shared datasets directly within their Snowflake environment rather than building separate extraction and ingestion workflows. Snowflake’s Secure Data Sharing infrastructure supports sharing across clouds and regions, allowing providers to distribute curated data products to multiple consumers.

For data providers, Snowflake Marketplace also supports public and private listings and multiple commercial models. Providers can offer free listings, trials, flat-fee access, subscriptions, or usage-based pricing depending on the data product and commercial arrangement.

Key Features

• Data marketplace: Provides a centralized environment for discovering third-party datasets, applications, and data products.
• Data sharing: Uses Snowflake’s secure data-sharing capabilities to provide access without traditional file-based transfers.
• Public listings: Allows providers to publish data products that can be discovered by Snowflake customers.
• Private listings: Supports controlled sharing of data products with specific consumers.
• Data products: Lets providers package datasets and related assets into managed marketplace offerings.
• Flexible pricing: Supports free, flat-fee, subscription-based, and usage-based pricing models.
• Cross-cloud sharing: Supports marketplace access across supported Snowflake cloud environments.
• Direct data access: Allows consumers to access shared data within their Snowflake account.
• Data monetization: Gives providers a way to commercialize proprietary datasets through marketplace listings.
• Usage management: Provides providers with information and controls around marketplace data usage.
• Trial access: Paid public listings can include trial access before purchase.

Pricing: Marketplace data products are priced by individual providers. Snowflake supports free, flat-fee, subscription, and usage-based pricing models rather than one fixed marketplace price.

G2 Rating: 4.3/5 for Snowflake Data Exchange on G2.

Also Read: Snowflake Alternatives and Competitors

#2 Databricks Marketplace

Databricks Marketplace is an open exchange where data providers, software vendors, and technology partners can publish offerings for Databricks customers. The marketplace has expanded beyond traditional datasets and now includes data products, AI models, notebooks, applications, and MCP servers.

The platform is closely integrated with the Databricks lakehouse and Unity Catalog, making it useful for teams that already use Databricks as their primary data and AI environment. Consumers can browse marketplace listings through Databricks or the Open Marketplace, while OpenSharing capabilities allow certain data products to be accessed from external platforms as well.

This makes Databricks Marketplace more than a conventional dataset directory. It provides a distribution layer for data and AI assets that can be incorporated into analytical, machine-learning, and application workflows without requiring organizations to establish separate data-sharing processes for every provider.

Key Features

• Data marketplace: Provides a central exchange for datasets, data products, software, and AI assets.
• Data product discovery: Lets users browse and evaluate offerings from data and technology providers.
• Lakehouse integration: Connects marketplace data with Databricks data and AI workflows.
• Open Marketplace: Allows users to browse marketplace products outside a Databricks workspace.
• OpenSharing: Supports secure data exchange across supported external platforms.
• AI models: Includes machine-learning and AI model offerings alongside datasets.
• Notebooks and applications: Providers can distribute additional Databricks-compatible assets through marketplace listings.
• Partner integrations: Partner Connect provides preconfigured connections to selected technology partners.
• External access: Certain tabular datasets can be accessed through tools such as Power BI, Excel, pandas, and Apache Spark.
• Data sharing: Helps providers distribute data products to consumers without building individual sharing relationships.

Pricing: Marketplace offerings are priced by individual providers. Listings can include free or paid products, with pricing dependent on the provider and data product.

G2 Rating: 4.6/5 for Databricks on G2.

Also Read: Databricks Alternatives and Competitors

#3 AWS Data Exchange

AWS Data Exchange is a cloud-based data marketplace that helps organizations find, subscribe to, and use third-party data within AWS. It provides a catalog of commercial and public data products and integrates those products with AWS services and data workflows.

The platform supports several delivery formats, including file-based datasets, APIs, Amazon Redshift datashares, Amazon S3 data, and AWS Lake Formation data permissions. This gives providers multiple ways to distribute their data while allowing consumers to choose a delivery mechanism that fits their existing architecture.

AWS Data Exchange is particularly useful when an organization already operates heavily within AWS. File-based data can be automatically exported to Amazon S3, while API datasets can be accessed through AWS credentials and SDKs. This reduces the need to create separate ingestion infrastructure for every external data provider.

Key Features

• Third-party data marketplace: Provides a catalog for discovering commercial and public data products.
• File datasets: Supports file-based data that can be exported to Amazon S3 or downloaded.
• API datasets: Allows subscribers to access provider APIs through AWS Data Exchange-managed endpoints.
• Amazon Redshift datashares: Provides read-only access to shared Redshift schemas, tables, views, and functions.
• Amazon S3 delivery: Automatically export new or updated file-based revisions to S3.
• Lake Formation integration: Supports data permissions through AWS Lake Formation.
• Data grants: Enables providers to grant access to specific AWS accounts for defined periods.
• Dataset versioning: Organizes changing data through datasets and revisions.
• AWS integration: Connects data products with the wider AWS analytics and machine-learning ecosystem.
• Provider publishing: Allows data providers to create and manage datasets and publish them as marketplace products.

Pricing: Providers set pricing for individual data products. AWS supports subscription-based and pay-as-you-go products, with pricing shown on individual product pages. Additional AWS data-transfer charges may apply.

G2 Rating: 4.2/5 from 16 reviews.

#4 Google Cloud Analytics Hub

Google Cloud Analytics Hub, now part of BigQuery data sharing, provides a managed environment for publishing, discovering, and subscribing to data and other analytical assets. It is designed around BigQuery and allows organizations to exchange data without requiring consumers to create traditional copies or ingestion pipelines.

The service supports internal data exchanges as well as public and commercial data providers. Publishers can make datasets available through exchanges, while subscribers can discover and use shared assets directly within their BigQuery environment.

This makes Analytics Hub particularly useful for organizations already using BigQuery that want to create governed data-sharing environments across departments, partners, or external providers. Google Cloud also supports exchanging assets beyond traditional datasets, including ML models and other analytics resources.

Key Features

• Data exchanges: Create managed environments for publishing and consuming shared data assets.
• BigQuery integration: Connect data sharing directly with BigQuery analytics workflows.
• Dataset discovery: Help users find available internal, public, and commercial datasets.
• Cross-organization sharing: Support controlled data exchange between organizations and partners.
• No-copy sharing: Let subscribers work with shared data without creating traditional copies of the source data.
• Data subscriptions: Allow users to subscribe to datasets published through exchanges.
• Commercial data: Provide access to datasets from commercial data providers.
• Analytics assets: Support sharing data, ML models, and other analytical assets.
• Centralized management: Provide a structured environment for managing published and subscribed data assets.
• Secure sharing: Apply BigQuery’s underlying access and security controls to shared data.
• Data provider ecosystem: Connect organizations with public, industry, Google, and commercial datasets.

Pricing: Publishers pay for storage according to BigQuery storage pricing, while subscribers pay for query processing according to their BigQuery pricing model.

G2 Rating: N/A.

#5 Datarade

Datarade is an independent data marketplace that helps businesses discover, compare, evaluate, and acquire external data products from multiple providers. Instead of being tied to a specific cloud data platform, it provides a marketplace-style discovery layer covering a wide range of data categories.

The platform allows buyers to browse datasets by attributes and category, compare providers, request samples, and obtain quotes. Datarade’s G2 profile currently describes the marketplace as covering more than 600 data categories and allowing buyers to compare providers and products.

Datarade also supports the supplier side of data commerce. Data providers can list their products and use Datarade’s Data Commerce Cloud to reach potential buyers across sales channels. This two-sided model makes it relevant to organizations looking both to source external data and to distribute commercial data products.

Key Features

• Data discovery: Search for external datasets across a wide range of categories and use cases.
• Provider comparison: Compare multiple data providers and products before making a purchasing decision.
• Data categories: Organizes external data into categories to simplify marketplace discovery.
• Data samples: Allows buyers to request samples before committing to a dataset.
• Quote requests: Helps buyers request pricing and information from relevant providers.
• Data reviews: Provides information that can help users evaluate data providers and products.
• Data provider marketplace: Gives suppliers a channel for listing and promoting their data products.
• Data commerce: Supports commercial workflows between data buyers and providers.
• Data sourcing: Helps teams centralize the process of finding external data vendors.
• Multiple data types: Covers areas such as financial, marketing, geospatial, and other commercial datasets.

Pricing: Pricing varies by data provider and product. Datarade’s marketplace itself does not publish a single standard dataset price; G2 currently lists product pricing as unavailable.

G2 Rating: 4.5/5 from 21 reviews.

#6 Dawex Data Exchange Platform

Dawex Data Exchange Platform is an enterprise data exchange solution designed to help organizations share, exchange, and monetize data. It supports controlled data flows between organizations, divisions, subsidiaries, partners, and other participants in a data ecosystem.

Unlike cloud-native marketplaces that are closely tied to a particular warehouse, Dawex focuses on the broader data-exchange process. Organizations can use the platform to create data marketplaces, manage data products, establish commercial relationships, and control how data is distributed.

The platform is also positioned around secure and compliant data exchange, making governance and controlled access important parts of the offering. G2 currently lists Dawex under Data Exchange Platforms but does not have enough reviews to provide a product rating.

Key Features

• Data marketplace: Create environments where organizations can publish and distribute data products.
• Data exchange: Facilitate controlled sharing of data between organizations and business units.
• Data monetization: Support commercial models for generating revenue from data assets.
• Data product management: Organize datasets and offerings for discovery and distribution.
• Data licensing: Support controlled commercial access to data products.
• Access management: Control which users or organizations can access particular data assets.
• Data governance: Apply policies and controls around data-sharing workflows.
• Secure data flows: Support controlled movement and exchange of data between participants.
• B2B data sharing: Facilitate data relationships between organizations and business partners.
• Data commercialization: Provide infrastructure for organizations developing data-driven revenue models.

Pricing: Custom pricing.

G2 Rating: N/A. G2 currently shows 0 reviews for Dawex Data Exchange Platform and states that there are not enough reviews to provide buying insight.

#7 Narrative

Narrative is a data commerce platform designed to simplify the process of buying, selling, and sharing data. It provides a marketplace environment where buyers can discover data assets, evaluate available options, and manage data acquisition workflows.

The platform is positioned around data commerce rather than being tied to a particular cloud warehouse. Buyers can browse data assets and use filtering capabilities to identify datasets that match specific requirements, while providers can use the platform to distribute and commercialize their data.

Narrative is therefore relevant for organizations that need an independent environment for external data sourcing or data monetization. Its marketplace approach can reduce the effort involved in finding and negotiating with multiple data providers separately.

Key Features

• Data marketplace: Provides an environment for discovering and acquiring external data products.
• Data discovery: Lets buyers browse available data assets and search for relevant sources.
• Data filtering: Helps buyers narrow datasets based on specific attributes and requirements.
• Data acquisition: Supports workflows for obtaining external data from marketplace providers.
• Data provider marketplace: Gives suppliers a channel for presenting and commercializing data assets.
• Data commerce: Provides infrastructure for managing relationships between data buyers and sellers.
• Data sharing: Supports distribution of data products through marketplace workflows.
• Data delivery: Connects purchased data with preferred systems and delivery methods.
• Provider management: Helps buyers identify and manage relationships with data suppliers.
• Data sourcing workflows: Provides a centralized environment for external data acquisition rather than relying on disconnected vendor searches.

Pricing: Custom/provider-specific pricing.

G2 Rating: 3.7/5 from 10 reviews.

How to Choose the Best Data Marketplace Tools

• Define your marketplace model: Decide whether you need an internal data marketplace, external data marketplace, or commercial marketplace for selling datasets.
• Check data discovery: Look for search, filtering, metadata, categories, samples, and other capabilities that make datasets easier to evaluate.
• Review delivery options: Check whether data can be accessed through APIs, files, direct shares, warehouses, or other delivery methods.
• Evaluate governance: Consider ownership, permissions, policies, licensing, and compliance requirements before selecting a platform.
• Assess provider capabilities: If you sell data, review publishing, pricing, licensing, customer management, and monetization features.
• Consider your data stack: Cloud-native marketplaces may provide simpler integration when your organization already relies heavily on Snowflake, Databricks, AWS, or BigQuery.
• Check self-service access: Make sure authorized users can discover and access data without requiring manual intervention for every request.
• Review pricing flexibility: For commercial data, check whether the marketplace supports subscriptions, usage-based pricing, one-time purchases, or negotiated deals.
• Assess scalability: Consider how the platform will handle increasing numbers of datasets, providers, consumers, and data products.
• Evaluate security: Review authentication, access controls, privacy mechanisms, and data-sharing policies for sensitive or commercially valuable datasets.

Conclusion

Data marketplace tools provide a structured way to make datasets easier to discover, access, share, and commercialize. They can reduce the friction between data producers and consumers while giving organizations more control over how data products are published and distributed.

The platforms in this list serve different environments. Snowflake Marketplace, Databricks Marketplace, AWS Data Exchange, and Google Cloud Analytics Hub are closely integrated with major cloud data platforms and can simplify access to data within existing analytics environments. Datarade, Dawex, and Narrative provide more independent approaches to external data discovery, data commerce, sharing, and monetization.

The best data marketplace depends on whether you are primarily consuming third-party datasets, sharing data internally, distributing data to partners, or building a commercial data business. Organizations should also consider delivery methods, governance, security, provider capabilities, pricing models, and integration with their existing data infrastructure.

Before selecting a platform, define who will use the marketplace, what types of data will be exchanged, how access should be controlled, and whether the primary objective is discovery, sharing, or monetization. The right data marketplace should make data easier to find and use without compromising governance or operational control.

Frequently Asked Questions

#1 What are data marketplace tools?

Data marketplace tools are platforms that help organizations discover, publish, share, buy, sell, or distribute datasets and other data products. They can also provide capabilities such as metadata, governance, access controls, licensing, and data delivery.

#2 What are the best data marketplace tools in 2026?

Some of the leading options include Snowflake Marketplace, Databricks Marketplace, AWS Data Exchange, Google Cloud Analytics Hub, Datarade, Dawex, and Narrative. The best option depends on whether the primary requirement is internal sharing, external data discovery, cloud-native access, or data monetization.

#3 What is a data marketplace?

A data marketplace is a centralized environment where data products can be discovered, accessed, shared, bought, or sold. It can operate within an organization or connect external data providers with data consumers.

#4 What is the difference between a data marketplace and a data catalog?

A data catalog primarily helps users discover and understand data assets within an organization. A data marketplace can include catalog capabilities but generally adds mechanisms for requesting, accessing, sharing, purchasing, selling, or distributing data products.

#5 Can companies sell data through a data marketplace?

Yes. Platforms such as Snowflake Marketplace, AWS Data Exchange, Databricks Marketplace, Datarade, and Dawex provide capabilities that can support data providers in publishing and commercializing data products. The available pricing and commercial models vary by platform.

#6 Can data marketplaces be used for internal data sharing?

Yes. Organizations can use data marketplace concepts to create self-service environments where employees discover governed datasets published by internal teams. This can reduce data silos and make approved data easier for analysts and other consumers to access.

#7 How do data marketplaces make money?

Commercial data marketplaces can generate revenue through transaction fees, provider subscriptions, listing fees, revenue sharing, or other commercial arrangements. Cloud marketplaces may also provide providers with different pricing models for individual data products.

#8 What types of data can be offered in a data marketplace?

Depending on the platform, marketplaces can include customer and business data, financial datasets, geospatial information, market research, demographic information, APIs, streaming data, machine-learning datasets, AI models, and other analytical assets.

#9 Are data marketplace tools open source?

Most major commercial data marketplaces are not open source. They are typically managed SaaS or cloud services. Organizations that need an open-source marketplace may need to build or customize their own data-sharing infrastructure.

#10 What should businesses consider before buying data from a marketplace?

Businesses should evaluate data quality, coverage, freshness, licensing rights, geographic scope, update frequency, delivery method, provider reputation, security, privacy requirements, and total cost before purchasing an external dataset.